@article{EmhardtJarodzkaBrandGruweletal.2020,
  author    = {Emhardt, Selina and Jarodzka, Halszka and Brand-Gruwel, Saskia and Drumm, Christian and Gog, Tamara van},
  title     = {Introducing eye movement modeling examples for programming education and the role of teacher's didactic guidance},
  series = {ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications},
  journal   = {ETRA '20 Short Papers: ACM Symposium on Eye Tracking Research and Applications},
  number    = {Art. 52},
  publisher = {ACM},
  address   = {New York},
  doi       = {10.1145/3379156.3391978},
  pages     = {1 -- 4},
  year      = {2020},
  abstract  = {In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with 'Eye Movement Modeling Examples' (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students' attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.},
  language  = {en}
}
@article{DrummEmhardtKoketal.2020,
  author    = {Drumm, Christian and Emhardt, Selina N. and Kok, Ellen M. and Jarodzka, Halzka and Brand-Gruwel, Saskia and van Gog, Tamara},
  title     = {How Experts Adapt Their Gaze Behavior When Modeling a Task to Novices},
  series = {Cognitive science},
  volume    = {44},
  journal   = {Cognitive science},
  number    = {9},
  publisher = {Wiley},
  address   = {Weinheim},
  issn      = {1551-6709},
  doi       = {10.1111/cogs.12893},
  pages     = {26},
  year      = {2020},
  abstract  = {Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts' (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts' changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts' natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts' behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts' automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.},
  language  = {en}
}